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Learning Types

32,670 papers (1 classified directly here)

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)
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Papers (including subtopics)

Improving Multilingual Neural Machine Translation by Utilizing Semantic and Linguistic Features ACL 2024 Improving Multi-party Dialogue Generation via Topic and Rhetorical Coherence EMNLP 2024 Improving Neural Biasing for Contextual Speech Recognition by Early Context Injection and Text Perturbation Interspeech 2024 Improving Neural Network Generalization on Data-Limited Regression with Doubly-Robust Boosting AAAI 2024 Improving Neural ODE Training with Temporal Adaptive Batch Normalization NeurIPS 2024 Improving Offline RL by Blending Heuristics ICLR 2024 Improving Panoptic Narrative Grounding by Harnessing Semantic Relationships and Visual Confirmation AAAI 2024 Improving Recall of Large Language Models: A Model Collaboration Approach for Relational Triple Extraction COLING 2024 Improving Referring Ability for Biomedical Language Models EMNLP 2024 Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts ACL 2024 Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective NeurIPS 2024 Improving robustness to corruptions with multiplicative weight perturbations NeurIPS 2024 Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective AISTATS 2024 Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps CVPR 2024 Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot Examples ACL 2024 Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment CVPR 2024 Improving Speech-Based Dysarthria Detection using Multi-task Learning with Gradient Projection Interspeech 2024 Improving Spoken Language Modeling with Phoneme Classification: A Simple Fine-tuning Approach EMNLP 2024 Improving Subgroup Robustness via Data Selection NeurIPS 2024 Improving Text Embeddings with Large Language Models ACL 2024 Improving the Adversarial Transferability of Vision Transformers with Virtual Dense Connection AAAI 2024 Improving the Fairness of the Min-Max Game in GANs Training WACV 2024 Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation CVPR 2024 Improving the Robustness of Distantly-Supervised Named Entity Recognition via Uncertainty-Aware Teacher Learning and Student-Student Collaborative Learning ACL 2024 Improving the Robustness of Large Language Models via Consistency Alignment COLING 2024